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: sequential or time-series modelling, reinforcement learning, generative modelling, or representation learning. Hands-on experience implementing ML algorithms from first principles using Python, C++, CUDA
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sampling strategies in Python and C++ Apply your framework to analyse real biological datasets to demonstrate robustness, interpretability, and practical impact Contribute to open-source software tools
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Midlands Graduate School Doctoral Training Partnership; | Birmingham, England | United Kingdom | 3 months ago
of economics, or a closely related discipline. A Master’s degree (with distinction/merit) is desirable. Previous experience with analysing large dataset using statistical and econometric software (e.g., Python
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(Python, C++) and computer (Linux, Windows) skills Excellent cooperation and communication skills You enjoy working within a diverse team in an international and interdisciplinary environment Very good
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field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a sound understanding of data evaluation Prior experience with single-cell data analysis
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Proficiency in at least one programming language, preferably Python; experience with scientific computing, numerical modeling, or machine-learning frameworks is an asset Strong analytical skills with a solid
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | 3 months ago
mechanisms. This will provide training in advanced quantitative methods, spatial data integration, uncertainty assessment, and reproducible coding in R or Python. Qualitatively, the project will use
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, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming (Python, C++) and computer (Linux, Windows) skills Excellent cooperation and communication skills
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machine learning, deep learning, or AI. Solid mathematical, algorithmic, or physics background, distinct analytical skills. Very good programming (Python, C++) and computer (Linux, Windows) skills